Unit Commitment Problem

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In my work on the Unit Commitment (UC) problem, I tackled one of the most critical challenges in power systems operations: scheduling the optimal combination of power generation units to meet electricity demand while minimizing operational costs and ensuring reliability. The UC problem is inherently complex due to its combinatorial nature, requiring advanced mathematical modeling and computational techniques.

My contributions centered around the development of a hybrid optimization framework that integrates a decomposition method with the tight model from the EGRET software suite. This approach effectively addresses the large-scale complexity of the UC problem by breaking it into smaller, computationally manageable subproblems without compromising much on the solution quality.

Key aspects of my work included:

• Modeling and Algorithm Design: Leveraged advanced mixed-integer programming techniques to enhance the performance of traditional UC models, ensuring accurate representations of generator constraints and operational limits.
• Scalability and Computational Speedup: Achieved significant reductions in computational time across four benchmark case studies, demonstrating the efficiency and robustness of the proposed approach for real-world applications.
• System-Wide Impact: Ensured reliable power system operation by integrating constraints related to energy reserves, ramp rates, and renewable energy variability.

This research directly contributes to improving decision-making processes in the energy sector by enabling more efficient and cost-effective scheduling of power generation units. It highlights the importance of advanced optimization techniques in addressing modern challenges such as the integration of renewable energy sources and the increasing demand for computational efficiency.

My work on this problem culminated in a comprehensive research paper that is currently under review for publication in the ESCAPE-35 proceedings. It demonstrates the potential of innovative optimization techniques to drive improvements in critical energy system operations.